Pivot Tables With Python Pandas Full Course

Name: Pivot Tables With Python Pandas Full Course
Rating: 4.6 (2 reviews)

Master Data Analysis with Pivot Tables in Python Using Pandas.

Created byKichere Magubu

Last updated 10/2024

English

What you'll learn

pivot() method in pandas
pivot_table() method in pandas
pivot_table() vs pivot() methods.
Data analysis with pivot tables

Course content

4 sections • 9 lectures • 1h 40m total length

Welcome0:52
Tips for effective learning0:08

pandas.pivot() part 18:36
data:
The DataFrame containing the data you want to reshape. This is the main input to the pivot() function.
Example: If you have a DataFrame with sales data, this parameter will take that DataFrame as input.
index:
This parameter specifies the column(s) to set as the new index for the pivoted DataFrame.
Use Case: Choose an index that identifies unique rows in the resulting DataFrame, such as "Date" or "Product ID".
columns:
This parameter indicates which column(s) should become the new columns in the pivoted DataFrame.
Use Case: Use a categorical variable, like "Region" or "Category", to create multiple columns in the new DataFrame.
pandas.pivot() part 24:28
values (optional):
This parameter specifies which column’s values will populate the newly created DataFrame.
Use Case: If you want to summarize sales data, you might specify the "Sales" column so that the pivot table shows total sales for each combination of index and column.

Requirements

Desire to Learn: A strong willingness to engage with the course material and practice new skills in data analysis.
Preferred Tools: A working installation of Python, preferably using Jupyter Lab or jupyter Notebook, for an interactive

Description

Learn how to use Pivot Tables in Python with Pandas to analyze and summarize data easily. This course is for anyone working with large datasets who wants to improve their data analysis skills. Whether you're a student, a data enthusiast, or a professional in the field, this course will provide you with the essential tools and techniques needed to unlock insights from your data.

In this course, you will:

Understand what pivot tables are and how they simplify data.
Use Pandas' pivot() method for simple data reshaping.
Use Pandas' pivot_table() to quickly summarize data.
Group, filter, and organize data for better insights.
Work with multi-level pivoting and large datasets.
Practice with real-world examples to reinforce your learning.

Additionally, you will learn best practices for data manipulation and visualization, ensuring you can present your findings effectively. The hands-on projects will enable you to apply the concepts learned throughout the course in practical scenarios, enhancing your understanding of data analytics. By the end, you'll know how to use pivot tables to make complex data easier to analyze, whether you're a beginner or an experienced analyst looking to refine your skills. Join us and take your data analysis expertise to the next level!

Who this course is for:

Individuals new to data analysis and those with experience in Python.
Aspiring data analysts and professionals seeking to enhance their data skills.
Students and researchers looking to analyze datasets.
Python enthusiasts interested in data manipulation and analysis.

Pivot Tables With Python Pandas Full Course

What you'll learn

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Course content

Tips For Effective Learning2 lectures • 1min

pandas.pivot()2 lectures • 13min

pandas.pivot_table()3 lectures • 34min

Bonus Functions: Reshape DataFrames with pandas.melt() and pandas.crosstab()2 lectures • 53min

Requirements

Description

Who this course is for: